首页> 外文期刊>Respiration: International Review of Thoracic Diseases >Sleep breathing flow characteristics as a sign for the detection of wakefulness in patients with sleep apnea.
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Sleep breathing flow characteristics as a sign for the detection of wakefulness in patients with sleep apnea.

机译:睡眠呼吸流动特征是检测睡眠呼吸暂停患者觉醒的标志。

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摘要

BACKGROUND: To improve the performance of simplified sleep studies, it is essential to properly estimate the sleep time. OBJECTIVES: Our aim is to estimate sleep efficiency on the basis of flow breathing signal characteristics. METHODS: Twenty subjects with sleep apnea-hypopnea syndrome diagnosed by polysomnography were studied. A characteristic pattern of flow signal defined our criteria for wakefulness and sleep. Sleep was analyzed in 2 different runs: (1) in the usual manner (neurological and respiratory variables), and (2) only the nasal cannula flow signal was displayed on the computer screen and the sleep and wakefulness periods were scored according to our criteria. At the end of the scoring process, all the signals were displayed on the screen to analyze the concordance. RESULTS: Three thousand and sixty-nine screens were analyzed. The polysomnography sleep efficiency measured was 80.8%. The estimated sleep efficiency measured by nasal prongs was 78.9%. The detection and concordance of wakefulness had a sensitivity of 58.7%, a specificity of 96.4%, a positive predictive value of 81.3% and a negative predictive value of 89.6%. CONCLUSIONS: Our criteria for sleep and wakefulness based on airflow waveform morphology are a helpful parameter for estimating sleep efficiency in a simplified sleep study.
机译:背景:为了提高简化睡眠研究的性能,必须正确估计睡眠时间。目的:我们的目的是根据呼吸信号的特征来估计睡眠效率。方法:对20例经多导睡眠图诊断为睡眠呼吸暂停低通气综合征的受试者进行研究。流量信号的特征模式定义了我们的清醒和睡眠标准。在2种不同的运行中对睡眠进行了分析:(1)以通常的方式(神经和呼吸系统变量)进行,并且(2)在计算机屏幕上仅显示鼻导管流量信号,并根据我们的标准对睡眠和清醒期进行评分。在计分过程结束时,所有信号都显示在屏幕上以分析一致性。结果:分析了369个屏幕。测得的多导睡眠图睡眠效率为80.8%。经鼻叉测量的估计睡眠效率为78.9%。觉醒的检测和一致性灵敏度为58.7%,特异性为96.4%,阳性预测值为81.3%,阴性预测值为89.6%。结论:我们基于气流波形形态的睡眠和清醒标准是在简化的睡眠研究中评估睡眠效率的有用参数。

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